From acba270f9bda5ef672fa0c2758d2997fcddaa517 Mon Sep 17 00:00:00 2001 From: Vijay Janapa Reddi Date: Fri, 18 Jul 2025 10:55:26 -0400 Subject: [PATCH] =?UTF-8?q?=F0=9F=94=A7=20Fix=20MLOps=20over-emphasis=20an?= =?UTF-8?q?d=20repetitive=20differentiation=20statements?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ✂️ Reduced MLOps Focus: - Renamed 'MLOps & Production' → 'Development Tools' - Removed redundant 'MLOps Community' link - Focuses on practical development tools instead 🎯 Made Framework Differentiations Distinct: - Micrograd: 'shows you the math, TinyTorch shows you the systems' - Tinygrad: 'optimizes for speed, TinyTorch optimizes for learning' - NNFS: 'focuses on algorithms, TinyTorch focuses on complete systems engineering' 💡 Benefits: - Each differentiation now highlights specific strengths vs repetitive vehicle analogy - Less MLOps emphasis (appears in course already) - More concise and memorable comparisons Result: Cleaner resource organization with unique, specific differentiations that avoid repetition and over-emphasis on any single topic. --- book/resources.md | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/book/resources.md b/book/resources.md index 03b505d7..1ffdab3c 100644 --- a/book/resources.md +++ b/book/resources.md @@ -54,13 +54,13 @@ While TinyTorch teaches you to build complete ML systems from scratch, these res ### **Minimal Frameworks** - **[Micrograd](https://github.com/karpathy/micrograd)** by Andrej Karpathy - *Minimal autograd engine in 100 lines. **Micrograd teaches engine parts, TinyTorch teaches you to design the whole vehicle and drive it.*** + *Minimal autograd engine in 100 lines. **Micrograd shows you the math, TinyTorch shows you the systems.*** - **[Tinygrad](https://github.com/geohot/tinygrad)** by George Hotz - *Performance-focused educational framework. **Tinygrad optimizes for speed, TinyTorch optimizes for learning systems thinking.*** + *Performance-focused educational framework. **Tinygrad optimizes for speed, TinyTorch optimizes for learning.*** - **[Neural Networks from Scratch](https://nnfs.io/)** by Harrison Kinsley - *Math-heavy implementation approach. **NNFS teaches you the engine parts, TinyTorch teaches you to design the whole vehicle and drive it.*** + *Math-heavy implementation approach. **NNFS focuses on algorithms, TinyTorch focuses on complete systems engineering.*** --- @@ -73,13 +73,10 @@ While TinyTorch teaches you to build complete ML systems from scratch, these res - **[PyTorch Documentation: Extending PyTorch](https://pytorch.org/docs/stable/notes/extending.html)** *Custom operators and autograd functions - apply your TinyTorch knowledge* -### **MLOps & Production** +### **Development Tools** - **[Papers With Code](https://paperswithcode.com/)** *Research papers with implementation code - apply your skills to reproduce results* -- **[MLOps Community](https://mlops.community/)** - *Production ML engineering discussions and best practices* - - **[Weights & Biases](https://wandb.ai/)** *Experiment tracking and model management - scale your TinyTorch training*